Abstract: There is provided a data processing device 10 that performs a convolution operation of two pieces of input data of 2M×N bits (N is a positive integer and M is a natural number) width with a minimum accuracy of the convolution operation being N bits, and performs processing corresponding to a plurality of the consecutive M, the data processing device 10 including: a product-sum operation unit 101 that performs a product-sum operation according to the value of M; a shifter 102 that performs shift processing on a result of a product-sum operation of the product-sum operation unit 101 in a case where the value of M is not 0; an addition unit 103 that performs addition processing on each output of the shifter 102 or the product-sum operation unit 101 according to the value of M; a selector 105 that selects an output from the addition unit 103 according to the value of M; a cumulative addition unit 106 that cumulatively adds the outputs from the selector 105; and a cumulative addition memory 107 that stores outputs

Abstract: An image forming apparatus includes a brush member that includes a fiber yarn and that can come into contact with a surface of an image bearing member at a downstream of a transfer member and at an upstream of a charging member in a rotation direction of the image bearing member. The image bearing member and the brush member are relatively movable to a first position at which a leading end of the fiber yarn separates from the surface of the image bearing member, and a second position at which the leading end of the fiber yarn comes into contact with the surface of the image bearing member. A relative approaching direction of the brush member to the image bearing member upon relative movement from the first position to the second position is a direction from a downstream side to an upstream side in the rotation direction.

Abstract: An impedance measurement apparatus is provided for measuring impedance of a secondary battery. The impedance measurement apparatus includes a measurement unit and a switching unit. The measurement unit is capable of measuring the impedance of the secondary battery using a plurality of measurement modes differing in measurement condition. The switching unit is configured to switch between the plurality of measurement modes based on a comparison between a correlating parameter, which correlates with the impedance of the secondary battery, and a threshold value.

Abstract: A burst traffic detection device includes a packet receiver configured to receive packets from a network, a flow specification device configured to specify, in accordance with header information of the packets, flow rules, a flow information storage device configured to store flow information of the specified flow rules, a statistical information storage device configured to store statistical information including the total number of packets for each flow rule and/or the total number of bytes for each flow rule, a burst detection device configured to detect the occurrence of burst traffic in accordance with the statistical information, and a detection count storage device configured to store the number of times of the occurrence of burst traffic.

Abstract: A secondary battery includes a positive electrode, a negative electrode, an electrolyte layer, and a shut layer. The electrolyte layer is made of an electrolyte material having lithium ion conductivity. The shut layer contains a lithium ion conductive solid material having lithium ion conductivity. The electrolyte layer is interposed between the negative electrode and the shut layer. The shut layer is made of only a lithium ion conductive solid material or a mixture of the lithium ion conductive solid material. The lithium ion conductive solid material is at least one of a pyrochlore solid electrolyte, a NASICON solid electrolyte, and a perovskite solid electrolyte. The lithium ion conductive solid material has a larger decrease in lithium ion conductivity when in contact with lithium metal than the electrolyte material.

Abstract: An embodiment is a traffic monitoring device configured to acquire traffic statistical information of a flow in the monitoring target network, determine whether the acquired traffic statistical information satisfies a predetermined reference for failure detection, capture packets of the flow determined to satisfy the predetermined reference as packets at the time of failure occurrence in the flow, and dynamically update the predetermined reference while the device is still acquiring traffic statistical information of the flow in the monitoring target network.

Abstract: A SOH indicating a deterioration degree of a secondary battery is estimated. SOH information of the secondary battery is acquired. Information indicating a battery state of the secondary battery and information indicating the battery state having a correlation with the SOH higher than a predetermined correlation are acquired. A SOH estimation model is built by synthesizing a regression model using a variance-covariance matrix, in which the SOH information is defined as an output, and the information indicating the battery state that has the correlation with the SOH higher than the predetermined correlation is defined as an input The SOH is estimated by inputting information indicating a current battery state of the secondary battery into the SOH estimation model.

Abstract: A solid electrolyte for a secondary battery includes an oxide-based solid electrolyte having a pyrochlore structure represented by a composition formula of Aa2??Ab(1+?)/3B2O7??X?, where Aa is an alkali metal, Ab contains at least a lanthanide, B is a cationic metal different from Aa and Ab, and X is an anion that is substitutable with an O atom constituting the pyrochlore structure.

Abstract: An electricity storage device includes a negative electrode, a positive electrode, a polymer electrolyte layer provided between the negative electrode and the positive electrode and having lithium ion conductivity, an electrolyte layer provided between the negative electrode and the positive electrode and having lithium ion conductivity, and an alloy-forming layer capable of forming an alloy with lithium. The polymer electrolyte layer contains cyclic polycarbonate and chain polycarbonate. The polymer electrolyte layer contains lithium salt. Concentration of lithium salt in the polymer electrolyte layer is 3 mol/L or more. The polymer electrolyte layer and the alloy-forming layer are formed at least on a surface of the electrolyte layer facing the negative electrode. The alloy-forming layer is located closer to the electrolyte layer than the polymer electrolyte layer. The polymer electrolyte layer is located closer to the negative electrode than the alloy-forming layer.

Abstract: An object detection device subjects fixed-length data having a decimal point position set therein to an arithmetic processing corresponding to respective layers in a plurality of layers configuring a multilayer neural network to which an input image is input, the arithmetic processing being performed in accordance with a processing algorithm for the multilayer neural network to which an input image is input. In the arithmetic processing, the object detection device counts the upper limit number of saturations, which is a number of times that upper limit value of a value range determined by the decimal point position is exceeded, and the lower limit number of saturations, which is a number of times that the lower limit value of the value range is not reached.

Abstract: An electricity storage device includes a negative electrode, a positive electrode, a polymer electrolyte layer provided between the negative electrode and the positive electrode, an alloy-forming layer capable of forming a lithium alloy, and a polymer electrolyte layer having lithium ion conductivity. The polymer electrolyte layer has lithium ion conductivity. The polymer electrolyte layer and the alloy-forming layer are formed at least on a side of the negative electrode of the electrolyte layer. The alloy-forming layer is located closer to the electrolyte layer. The polymer electrolyte layer is located closer to the negative electrode.

Abstract: In a learning device, an inference means performs an inference with respect to training data using an inference model, and outputs a class score. A weight calculation means calculates each weight using a weight function which rapidly increases faster than a linear function for the class score that is over-estimated or under-estimated, based on output the class score. A weight sum calculation means calculates a total of weights over a mini-batch included in a predetermined number of training data. A regularization term calculation means calculates a regularization term by applying a rescale function which is a monotonically increasing function gradually increasing more than a linear function, to the regularization term. An optimization means optimizes the inference model using a total loss including the regularization term.

Abstract: A packet capturing device includes: a normal capturing function unit that accumulates packets that match conditions of a target flow registered in a flow table in response to an instruction to start capturing from outside and converts the accumulated packets into a captured file, from among packets flowing through a network that is a monitoring target; and a short-term capturing function unit that accumulates the packets received from the network during a period needed by the conditions of the target flow to be registered in the flow table from arrival of the instruction to start capturing and converts the accumulated packets into a captured file

Abstract: An embodiment is a packet capture device including a first local timer synchronized with an external global timer, a second local timer, a time stamp assign unit for assigning a time stamp to a inputted packet signal based on the second local timer, a filter unit for selecting the packet signal to which the time stamp is assigned, a capture file generation unit for receiving the selected packet signal, and a storage unit for storing a capture file generated in the capture file generation unit, wherein the capture file generation unit calculate a difference between a timer value of the first local timer and a timer value of the second local timer to correct the time stamp value on the basis of the difference.

Abstract: An object detecting device includes: an overall processing unit configured to perform object detection processing on an input image; an allocation processing unit configured to determine a segmented image for each frame which is subject to object detection among the plurality of segmented images in advance in a cycle of N frames, and reserve the determined segmented image; a selection processing unit configured to select and output, for each frame, some of the segmented images that are subject to object detection among the plurality of segmented images based on a reservation result from the allocation processing unit; a division processing unit configured to perform object detection processing on each of the segmented images output from the selection processing unit; and a synthesizing processing unit configured to synthesize an object detection result from the overall processing unit and an object detection result from the division processing unit.

Abstract: A first aspect of the present disclosure is a convolutional neural network inference processing device that performs processing in a convolutional neural network including a plurality of convolution layers and a residual layer that adds intermediate data related to the plurality of convolution layers as an addition target to a processing result by the plurality of convolution layers for each tile that is data obtained by dividing input data into a predetermined size, the convolutional neural network inference processing device including an inconsistency data storage unit that stores inconsistency data that is data at a portion where there is inconsistency between the processing result and the intermediate data, a past layer data storage unit that stores past layer data that is an addition target in a residual layer generated using inconsistency data related to the tile for which processing has been performed in a past and the intermediate data, and a processing unit that performs processing by the plurality o

Abstract: The dataset supply unit supplies a learning dataset. The recognition unit outputs the recognition result for the recognition object data in the supplied learning dataset. Further, the intersection matrix computation unit computes the intersection matrix based on the learning dataset. The recognition loss computation unit computes the recognition loss using the recognition result, the intersection matrix, and the correct answer data given to the recognition object data. Then, the updating unit updates the parameters of the recognition unit based on the recognition loss.

Abstract: An embodiment packet capture method includes steps of imparting a flag for each data of a received and divided packet, a step of writing the data in a ring buffer, steps of issuing a failure detection trigger when a cumulative value of the number of bytes of the packet within a period of failure detection exceeds a failure detection threshold value, steps of stopping writing to the ring buffer when writing to the ring buffer reaches or exceeds a writing stop address determined on the basis of the failure detection trigger, a step of reading data sequentially from the writing stop address, and steps of outputting a packet capture depending on the result determined based on the flags of the read data.

Abstract: A packet capture device a packet analysis unit that analyzes an input packet; a flow identification unit that identifies a flow as a capture target; an output adjustment unit that adjusts a packet amount of the flow as the capture target to be output to a storage unit; a buffer unit that temporarily accumulates a packet of the flow as the capture target; and the storage unit that stores the packet of the flow as the capture target, in which the output adjustment unit is configured to decide whether to output the packet of the flow as the capture target to the storage unit for each predetermined measurement interval on the basis of a measurement result of the packet amount of the capture target in a predetermined measurement interval, and discard the packet not to be output to the storage unit.

Abstract: When an output feature map to be an output of convolution processing is output, the output feature map is output to a storage unit for each of divided small regions. When each small region is output to the storage unit, in a case where a feature included in the small region is the same as a predetermined feature or a feature of a small region output in the past, the predetermined feature or the feature of a small region output in the past is compressed and output to the storage unit.